By Adnan Acan (auth.), Günther R. Raidl, Jens Gottlieb (eds.)
This booklet constitutes the refereed court cases of the fifth ecu convention on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2005, held in Lausanne, Switzerland in March/April 2005.
The 24 revised complete papers provided have been conscientiously reviewed and chosen from sixty six submissions. The papers hide evolutionary algorithms in addition to comparable methods like scatter seek, simulated annealing, ant colony optimization, immune algorithms, variable local seek, hyperheuristics, and estimation of distribution algorithms. The papers take care of representations, research of operators and health landscapes, and comparability algorithms. one of the combinatorial optimization difficulties studied are graph coloring, quadratic project, knapsack, graph matching, packing, scheduling, timetabling, lot-sizing, and the touring salesman challenge.
Read or Download Evolutionary Computation in Combinatorial Optimization: 5th European Conference, EvoCOP 2005, Lausanne, Switzerland, March 30 - April 1, 2005. Proceedings PDF
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Additional resources for Evolutionary Computation in Combinatorial Optimization: 5th European Conference, EvoCOP 2005, Lausanne, Switzerland, March 30 - April 1, 2005. Proceedings
The events are pre-sorted in descending order of their priority. If the meetings are present in a dataset, ties in priority are broken by descending order of the number of trainers involved to ensure that the meetings have been considered early in schedule construction. The upper bound of all possible schedules for each problem instance represents the solution for the relaxed version of the problem where all constraints on availability of trainers and rooms, room types and capacities, on starting times for the events and their time windows are ignored (see  fore more details).
PhD thesis, University of Michigan, Ann Harbor, Michigan, (1967). 9. : Parameter Control in Evolutionary Algorithms IEEE Transactions on Evolutionary Computation, 3, 2, (1999), 124-141. 10. : Evolutionary Computation: Comments on the History and Current State, IEEE Transactions on Evolutionary Computation, 1, 1, (1997), 3-17. 11. : On Stopping Criteria for Genetic Algorithms. , Labidi, S. ): Advances in Artificial Intelligence SBIA 2004 Lecture Notes in Artificial Intelligence Vol. 3171 Springer-Verlag, Berlin Heidelberg New York (2004) 405–413.
European Journal of Operational Research 153 (2004) 3-27 2. : Hyperheuristics: An Emerging Direction in Modern Search Technology. A. ): Handbook of Metaheuristics. Kluwer Academic Publishers, Boston Dordrecht London (2003) 457-474 3. : A Hyperheuristic Approach to Scheduling a Sales Summit. , Erben, W. ): Practice and Theory of Automated Timetabling III: PATAT2000. Lecture Notes in Computer Science, Vol. 2079. Springer-Verlag, Berlin Heidelberg New York (2000) 176-190 4. : Adaptive Problem-Solving for Large-Scale Scheduling Problems: A Case Study.